3,567 research outputs found

    Mobile Device Background Sensors: Authentication vs Privacy

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    The increasing number of mobile devices in recent years has caused the collection of a large amount of personal information that needs to be protected. To this aim, behavioural biometrics has become very popular. But, what is the discriminative power of mobile behavioural biometrics in real scenarios? With the success of Deep Learning (DL), architectures based on Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), such as Long Short-Term Memory (LSTM), have shown improvements compared to traditional machine learning methods. However, these DL architectures still have limitations that need to be addressed. In response, new DL architectures like Transformers have emerged. The question is, can these new Transformers outperform previous biometric approaches? To answers to these questions, this thesis focuses on behavioural biometric authentication with data acquired from mobile background sensors (i.e., accelerometers and gyroscopes). In addition, to the best of our knowledge, this is the first thesis that explores and proposes novel behavioural biometric systems based on Transformers, achieving state-of-the-art results in gait, swipe, and keystroke biometrics. The adoption of biometrics requires a balance between security and privacy. Biometric modalities provide a unique and inherently personal approach for authentication. Nevertheless, biometrics also give rise to concerns regarding the invasion of personal privacy. According to the General Data Protection Regulation (GDPR) introduced by the European Union, personal data such as biometric data are sensitive and must be used and protected properly. This thesis analyses the impact of sensitive data in the performance of biometric systems and proposes a novel unsupervised privacy-preserving approach. The research conducted in this thesis makes significant contributions, including: i) a comprehensive review of the privacy vulnerabilities of mobile device sensors, covering metrics for quantifying privacy in relation to sensitive data, along with protection methods for safeguarding sensitive information; ii) an analysis of authentication systems for behavioural biometrics on mobile devices (i.e., gait, swipe, and keystroke), being the first thesis that explores the potential of Transformers for behavioural biometrics, introducing novel architectures that outperform the state of the art; and iii) a novel privacy-preserving approach for mobile biometric gait verification using unsupervised learning techniques, ensuring the protection of sensitive data during the verification process

    Who sets the conservation agenda?

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    The global conservation agenda is constituted and organised through international conferences, congresses, and other fora. These events are key to the construction of established definitions, goals and practices of conservation, and serve as spaces for open debate and contestation of values and interests. Past work has explored such events through direct participation in their public aspects. However, to date there has been little empirical investigation of the decision making that occurs behind the scenes, and how the complex network of actors interacts to shape global conservation. In this thesis we set out four empirical investigations into the shaping of the global conservation agenda using International Union for Conservation of Nature’s (IUCN) motions process, a unique cross-sector deliberative policy process, as a case study. We investigated how the content raised by organisations has changed over time and is linked to key characteristics such as sector, size, region and preferred language. We then examined motion debates to uncover the discourses mobilised in shaping policy, and what strategies are utilised to generate change. The voting records of participating actors were analysed to uncover the key conceptual divides within IUCN’s Membership, as well as how position on these issues is related to key characteristics. Finally, participation in the motions process was investigated, identifying the type of actors that most influence IUCN’s motions process. We found markedly different interests and ideas shaping global conservation policy, and a key divide over the legitimacy of IUCN’s motions process making demands of nation states. We found that an overarching commitment to consensus in resolving disputes within the motions process seems to create a barrier to properly addressing key conceptual divides within the Membership. Our results prove the worth of investigating the less visible components of global conservation fora and set out a mixed methods approach to incorporating conceptually distinct results

    Computer-Aided Drug Design and Drug Discovery: A Prospective Analysis

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    In the dynamic landscape of drug discovery, Computer-Aided Drug Design (CADD) emerges as a transformative force, bridging the realms of biology and technology. This paper overviews CADDs historical evolution, categorization into structure-based and ligand-based approaches, and its crucial role in rationalizing and expediting drug discovery. As CADD advances, incorporating diverse biological data and ensuring data privacy become paramount. Challenges persist, demanding the optimization of algorithms and robust ethical frameworks. Integrating Machine Learning and Artificial Intelligence amplifies CADDs predictive capabilities, yet ethical considerations and scalability challenges linger. Collaborative efforts and global initiatives, exemplified by platforms like Open-Source Malaria, underscore the democratization of drug discovery. The convergence of CADD with personalized medicine offers tailored therapeutic solutions, though ethical dilemmas and accessibility concerns must be navigated. Emerging technologies like quantum computing, immersive technologies, and green chemistry promise to redefine the future of CADD. The trajectory of CADD, marked by rapid advancements, anticipates challenges in ensuring accuracy, addressing biases in AI, and incorporating sustainability metrics. This paper concludes by highlighting the need for proactive measures in navigating the ethical, technological, and educational frontiers of CADD to shape a healthier, brighter future in drug discovery

    Determination of breeding criteria for gait proficiency in leisure riding and racing dromedary camels: a stepwise multivariate analysis of factors predicting overall biomechanical performance

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    To date, the biomechanical dynamics in camelids have not been addressed, although it might be a factor that can affect selection and breeding in this species. Therefore, the aim of this article is to conduct curve fitting and discriminant canonical analysis to identify the mathematical function that best captures the dynamics of camel locomotion and to study the impact of kinematic, morphometric, physiological, and phaneroptic variables on gait performance in leisure riding and racing activities in dromedaries, respectively. The cubic function emerged as the most suitable mathematical model to represent the locomotive behavior of camels. Various factors were found to play a pivotal role in the athletic performance of leisure riding and racing dromedary camels. Concretely, angular measurements at the distal fore and rear extremity areas, pelvis inclination, relative volume of the hump, impact forces of the front limbs, post-neutering effects, and the kinematic behavior of the scapula, shoulder, carpus, hip, and foot are the factors that greatly impact gait performance in leisure riding and racing camels. The biomechanical performance at these specific body regions has a profound impact on weight absorption and minimization of mechanic impact during camel locomotion, static/dynamic balance, force distribution, energy of propulsion, movement direction and amplitude, and storage of elastic strain in leisure riding and racing dromedaries. In contrast, other animal- and environment-dependent factors do not exert significant influence on camel gait performance, which can be attributed to species-specific, inherited adaptations developed in response to desert conditions, including the pacing gait, broad foot pads, and energy-efficient movements. The outcomes of our functional data analysis can provide valuable insights for making informed breeding decisions aimed at enhancing animal functional performance in camel riding and racing activities. Furthermore, these findings can open avenues for exploring alternative applications, such as camel-assisted therapy

    Metabolic pathways and therapeutic opportunities in the chronic lymphocytic leukemia microenvironment

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    This study delves into the intricate metabolic dynamics of chronic lymphocytic leukaemia (CLL) within the tumour microenvironment (TME) of lymphoid tissues. Unlike the traditional focus on quiescent CLL cells in peripheral blood, this study aims to unravel complex metabolic behaviour of CLL cells in the lymph node compartment, where CLL cells divide and become activated.Utilizing state-of-the-art methods, such as metabolomics, transcriptomics, and fluxomics, we found that interaction of CLL cells with adjacent cells within the TME results in significant metabolic alterations. Particularly, we discovered a shift towards glutamine dependency of CLL cells upon TME-related stimulation. Such metabolic alterations impact sensitivity of these leukaemia cells to treatments, especially to specific apoptosis inducing agents, such as venetoclax, which has become the cornerstone of CLL treatment. The study demonstrates that by targeting specific metabolic pathways, such as the electron transport chain, CLL cells can be sensitized to venetoclax treatment. This finding can be exploited for the development of innovative strategies in order to overcome drug resistance.Additionally, the thesis explores the effects of mitochondrial glutamine transporters and the broader implications of lipid metabolism alterations in CLL. It also probes into the role of key genetic factors, such as p53, in the metabolic regulation of CLL and other B cell malignancies, unveiling new insights into potential therapeutic vulnerabilities.Conclusively, this research not only fills critical gaps in our understanding of CLL metabolism within the TME but also paves the way for novel, targeted therapeutic interventions. By linking metabolic alterations to treatment responses, it sets the stage for more effective, personalized approaches in the management of CLL

    From oral infection to autoimmunity : studies of antibodies and B cells on the path towards rheumatoid arthritis

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    Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease characterized by inflammation of the synovial joints, which can lead to irreversible joint destruction and disability if not treated properly. The majority of patients are seropositive, defined by presence of autoantibodies, i.e., rheumatoid factor (RF) and/or anti-citrullinated protein antibodies (ACPA). My thesis work focuses on ACPA+ RA, which is known for its more severe disease course. ACPA can be detected in the blood years before clinical signs of RA and were for a long time suggested to contribute to pathology, an hypothesis which is currently under debate. Still, the presence of ACPA, and the successful use of B-cell depleting therapies in RA, points to an important role for autoantibodies and B cells in the development of RA. Notably, most known risk factors for RA, in particular smoking and HLA-DRB1 shared epitope (SE) alleles, are specifically linked to onset of ACPA+ RA. My studies have investigated another potential risk factor for RA, namely the oral pathogen Porphyromonas gingivalis (Pg), one of the main drivers of periodontitis (PD). PD is a common disease that is driven by dysbiosis in the oral cavity triggering gingivitis and eventually leads to destruction of the jawbone and toothsupporting surrounding soft tissues. PD has a higher prevalence in RA than in the general population. Interestingly, Pg has the unique characteristic to express its own citrullinating enzyme and has therefore been suggested to contribute to the generation of RA autoantigens, break of tolerance and systemic ACPA production. The overall aims of my thesis were: 1) to determine if presence of antibodies against the Pg virulence factor RgpB could serve as biomarker to identify patients with PD at increased risk for systemic autoimmunity and onset of RA; 2) to explore the gingiva as a site for ACPA production, and Pg as a driver of the ACPA response; and 3) to phenotypically characterise peripheral blood B cells in the risk-RA phase, to understand B-cell dysregulation prior to RA onset. Investigating the anti-Rgp IgG response in two PD cohorts showed that this antibody response could only poorly discriminate PD from controls. However, elevated anti-Rgp IgG levels defined a subset of PD patients with active gingivitis and advanced marginal jawbone loss. We also showed a higher prevalence of ACPA+ individuals in PD versus controls, and higher anti-Rgp IgG levels in ACPA+ versus ACPA- individuals. Moreover, in a prospective study of ACPA+ individuals at increased risk for RA we found significantly higher anti-Rgp IgG levels compared to controls, but antibody levels did not differ between those who progressed to arthritis and those who remained arthritis free. Generation of monoclonal antibodies derived from RA gingival tissue B cells demonstrated the presence of citrulline-reactive clones binding epitopes on both Pg and self-proteins, and this cross-reactivity was also shown for an RA peripheral blood-derived ACPA+ clone. Investigating the serum polyclonal response, 11% of patients with early RA were positive for antibodies targeting a citrullinated Pg peptide. When assessing peripheral blood B cells in ACPA+ Risk-RA individuals, we detected dysregulation of B-cell subsets already before clinical onset, specifically showing loss of CD27 on class-switched IgG+ memory B cells, a feature previously described in autoimmunity. Collectively, these studies can link anti-Pg antibodies – as a proxy for Pg infection – to severe forms of PD and to the ACPA response, but not to arthritis onset. Thus, suggesting Pg-infection could be an early event in the natural history of RA, possibly triggering ACPA production in the gum mucosa by mechanisms of molecular mimicry. Moreover, the detection of B-cell changes already in the at-risk phase, supports the use of immune monitoring to capture individuals at risk of RA onset, that may benefit the most from pre-clinical intervention

    Drug induced Parkinson’s: A comprehensive review of the issues and measures required to tackle the same

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    Drug-inducedParkinsonism(DIP) closelyresemblesParkinson'sdisease(PD)inmotorsymptoms butiscausedbyspecificmedicationsdisruptingdopaminereceptorsandneurotransmitterbalance. PD involves a complex interplay of genetic, environmental, and biochemical factors resulting in the gradual degeneration of dopaminergic neurons. Environmental toxins and genetic mutations, such as LRRK2 and SNCA, contribute to the risk of developing PD. DIP primarily occurs due to the obstruction of dopamine receptors by certain drugs, notably antipsychotics and antiemetics, affecting dopamine transmission and causing Parkinsonian symptoms. Toxin-induced Parkinsonism(TIP)arisesfromexposuretosubstanceslikemanganese,herbicides,pesticides,and specific drugs, disrupting dopaminergic pathways and altering neurotransmission. This study examines various cases of DIP, emphasizing the significance of timely identification and intervention. A thorough understanding and proactive management of DIP are crucial for alleviatingsymptomsandimprovingpatientoutcomes.Healthcareprofessionalsneedtodiligently monitor patients using medications associated with DIP, adjust treatment plans, and educate patientsaboutpotentialsideeffects. Further researchisimperativetounravelthepathophysiology of DIP, considering genetic, environmental, and drug-related factors, to enhance clinical practices and optimize patient care. Addressing DIP requires a multifaceted approach, including early recognition, thoughtful management, and patient-centred care

    Combined Nutrition and Exercise Interventions in Community Groups

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    Diet and physical activity are two key modifiable lifestyle factors that influence health across the lifespan (prevention and management of chronic diseases and reduction of the risk of premature death through several biological mechanisms). Community-based interventions contribute to public health, as they have the potential to reach high population-level impact, through the focus on groups that share a common culture or identity in their natural living environment. While the health benefits of a balanced diet and regular physical activity are commonly studied separately, interventions that combine these two lifestyle factors have the potential to induce greater benefits in community groups rather than strategies focusing only on one or the other. Thus, this Special Issue entitled “Combined Nutrition and Exercise Interventions in Community Groups” is comprised of manuscripts that highlight this combined approach (balanced diet and regular physical activity) in community settings. The contributors to this Special Issue are well-recognized professionals in complementary fields such as education, public health, nutrition, and exercise. This Special Issue highlights the latest research regarding combined nutrition and exercise interventions among different community groups and includes research articles developed through five continents (Africa, Asia, America, Europe and Oceania), as well as reviews and systematic reviews

    Automated and Context-Aware Repair of Color-Related Accessibility Issues for Android Apps

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    Approximately 15% of the world's population is suffering from various disabilities or impairments. However, many mobile UX designers and developers disregard the significance of accessibility for those with disabilities when developing apps. A large number of studies and some effective tools for detecting accessibility issues have been conducted and proposed to mitigate such a severe problem. However, compared with detection, the repair work is obviously falling behind. Especially for the color-related accessibility issues, which is one of the top issues in apps with a greatly negative impact on vision and user experience. Apps with such issues are difficult to use for people with low vision and the elderly. Unfortunately, such an issue type cannot be directly fixed by existing repair techniques. To this end, we propose Iris, an automated and context-aware repair method to fix the color-related accessibility issues (i.e., the text contrast issues and the image contrast issues) for apps. By leveraging a novel context-aware technique that resolves the optimal colors and a vital phase of attribute-to-repair localization, Iris not only repairs the color contrast issues but also guarantees the consistency of the design style between the original UI page and repaired UI page. Our experiments unveiled that Iris can achieve a 91.38% repair success rate with high effectiveness and efficiency. The usefulness of Iris has also been evaluated by a user study with a high satisfaction rate as well as developers' positive feedback. 9 of 40 submitted pull requests on GitHub repositories have been accepted and merged into the projects by app developers, and another 4 developers are actively discussing with us for further repair. Iris is publicly available to facilitate this new research direction.Comment: 11 pages plus 2 additional pages for reference
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