194 research outputs found

    Patent Human Infections with the Whipworm, Trichuris trichiura, Are Not Associated with Alterations in the Faecal Microbiota

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    Background: The soil-transmitted helminth (STH), Trichuris trichiura colonises the human large intestine where it may modify inflammatory responses, an effect possibly mediated through alterations in the intestinal microbiota. We hypothesised that patent T. trichiura infections would be associated with altered faecal microbiota and that anthelmintic treatment would induce a microbiota resembling more closely that observed in uninfected individuals. Materials and Methods: School children in Ecuador were screened for STH infections and allocated to 3 groups: uninfected, T. trichiura only, and mixed infections with T. trichiura and Ascaris lumbricoides. A sample of uninfected children and those with T. trichiura infections only were given anthelmintic treatment. Bacterial community profiles in faecal samples were studied by 454 pyrosequencing of 16 S rRNA genes. Results: Microbiota analyses of faeces were done for 97 children: 30 were uninfected, 17 were infected with T. trichiura, and 50 with T. trichiura and A. lumbricoides. Post-treatment samples were analyzed for 14 children initially infected with T. trichiura alone and for 21 uninfected children. Treatment resulted in 100% cure of STH infections. Comparisons of the microbiota at different taxonomic levels showed no statistically significant differences in composition between uninfected children and those with T. trichiura infections. We observed a decreased proportional abundance of a few bacterial genera from the Clostridia class of Firmicutes and a reduced bacterial diversity among children with mixed infections compared to the other two groups, indicating a possible specific effect of A. lumbricoides infection. Anthelmintic treatment of children with T. trichiura did not alter faecal microbiota composition. Discussion: Our data indicate that patent human infections with T. trichiura may have no effect on faecal microbiota but that A. lumbricoides colonisation might be associated with a disturbed microbiota. Our results also catalogue the microbiota of rural Ecuadorians and indicate differences with individuals from more urban industrialised societies

    Android malware detection through generative adversarial networks

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    © 2019 John Wiley & Sons, Ltd. Mobile and cell devices have empowered end users to tweak their cell phones more than ever and introduce applications just as we used to with personal computers. Android likewise portrays an uprise in mobile devices and personal digital assistants. It is an open-source versatile platform fueling incalculable hardware units, tablets, televisions, auto amusement frameworks, digital boxes, and so forth. In a generally shorter life cycle, Android also has additionally experienced a mammoth development in application malware. In this context, a toweringly large measure of strategies has been proposed in theory for the examination and detection of these harmful applications for the Android platform. These strategies attempt to both statically reverse engineer the application and elicit meaningful information as features manually or dynamically endeavor to quantify the runtime behavior of the application to identify malevolence. The overgrowing nature of Android malware has enormously debilitated the support of protective measures, which leaves the platforms such as Android feeble for novel and mysterious malware. Machine learning is being utilized for malware diagnosis in mobile phones as a common practice and in Android distinctively. It is important to specify here that these systems, however, utilize and adapt the learning-based techniques, yet the overhead of hand-created features limits ease of use of such methods in reality by an end user. As a solution to this issue, we mean to make utilization of deep learning–based algorithms as the fundamental arrangement for malware examination on Android. Deep learning turns up as another way of research that has bid the scientific community in the fields of vision, speech, and natural language processing. Of late, models set up on deep convolution networks outmatched techniques utilizing handmade descriptive features at various undertakings. Likewise, our proposed technique to cater malware detection is by design a deep learning model making use of generative adversarial networks, which is responsible to detect the Android malware via famous two-player game theory for a rock-paper-scissor problem. We have used three state-of-the-art datasets and augmented a large-scale dataset of opcodes extracted from the Android Package Kit bytecode and used in our experiments. Our technique achieves F1 score of 99% with a receiver operating characteristic of 99% on the bytecode dataset. This proves the usefulness of our technique and that it can generally be adopted in real life

    Prevalence of physical and verbal aggressive behaviours and associated factors among older adults in long-term care facilities

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    BACKGROUND: Verbal and physical aggressive behaviours are among the most disturbing and distressing behaviours displayed by older patients in long-term care facilities. Aggressive behaviour (AB) is often the reason for using physical or chemical restraints with nursing home residents and is a major concern for caregivers. AB is associated with increased health care costs due to staff turnover and absenteeism. METHODS: The goals of this secondary analysis of a cross-sectional study are to determine the prevalence of verbal and physical aggressive behaviours and to identify associated factors among older adults in long-term care facilities in the Quebec City area (n = 2 332). RESULTS: The same percentage of older adults displayed physical aggressive behaviour (21.2%) or verbal aggressive behaviour (21.5%), whereas 11.2% displayed both types of aggressive behaviour. Factors associated with aggressive behaviour (both verbal and physical) were male gender, neuroleptic drug use, mild and severe cognitive impairment, insomnia, psychological distress, and physical restraints. Factors associated with physical aggressive behaviour were older age, male gender, neuroleptic drug use, mild or severe cognitive impairment, insomnia and psychological distress. Finally, factors associated with verbal aggressive behaviour were benzodiazepine and neuroleptic drug use, functional dependency, mild or severe cognitive impairment and insomnia. CONCLUSION: Cognitive impairment severity is the most significant predisposing factor for aggressive behaviour among older adults in long-term care facilities in the Quebec City area. Physical and chemical restraints were also significantly associated with AB. Based on these results, we suggest that caregivers should provide care to older adults with AB using approaches such as the progressively lowered stress threshold model and reactance theory which stress the importance of paying attention to the severity of cognitive impairment and avoiding the use of chemical or physical restraints

    Spinning, Spooning and the Seductions of Flirtatious Masculinity in Contemporary Politics

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    This paper explores the relationships between masculinity, flirtation and fantasy within the promotional arena of politics and PR. Flirtation is associated with coquetry and play, connoting a lack of seriousness, and in political flirtation, the desire to move between different opinions and ideas. Flirtation is often linked with femininity. Yet against a backdrop of masculinity in crisis, the study of flirtation, with its connotations of ambiguity and frustrated desire, is useful to explore the uncertainties of masculinities today. Dilemmas about flirtation as a tantalising performance resonate with misgivings about the seductive nature of political spin and the desire of politicians to woo audiences by flirting to the camera. Taking examples of politicians such as Tony Blair, Gordon Brown and Barack Obama, this paper discusses the possibilities of flirtatious masculinity as a counter-hegemonic strategy within the symbolic battleground of Western politics, a struggle largely played out in print and digital media

    In quest of a systematic framework for unifying and defining nanoscience

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    This article proposes a systematic framework for unifying and defining nanoscience based on historic first principles and step logic that led to a “central paradigm” (i.e., unifying framework) for traditional elemental/small-molecule chemistry. As such, a Nanomaterials classification roadmap is proposed, which divides all nanomatter into Category I: discrete, well-defined and Category II: statistical, undefined nanoparticles. We consider only Category I, well-defined nanoparticles which are >90% monodisperse as a function of Critical Nanoscale Design Parameters (CNDPs) defined according to: (a) size, (b) shape, (c) surface chemistry, (d) flexibility, and (e) elemental composition. Classified as either hard (H) (i.e., inorganic-based) or soft (S) (i.e., organic-based) categories, these nanoparticles were found to manifest pervasive atom mimicry features that included: (1) a dominance of zero-dimensional (0D) core–shell nanoarchitectures, (2) the ability to self-assemble or chemically bond as discrete, quantized nanounits, and (3) exhibited well-defined nanoscale valencies and stoichiometries reminiscent of atom-based elements. These discrete nanoparticle categories are referred to as hard or soft particle nanoelements. Many examples describing chemical bonding/assembly of these nanoelements have been reported in the literature. We refer to these hard:hard (H-n:H-n), soft:soft (S-n:S-n), or hard:soft (H-n:S-n) nanoelement combinations as nanocompounds. Due to their quantized features, many nanoelement and nanocompound categories are reported to exhibit well-defined nanoperiodic property patterns. These periodic property patterns are dependent on their quantized nanofeatures (CNDPs) and dramatically influence intrinsic physicochemical properties (i.e., melting points, reactivity/self-assembly, sterics, and nanoencapsulation), as well as important functional/performance properties (i.e., magnetic, photonic, electronic, and toxicologic properties). We propose this perspective as a modest first step toward more clearly defining synthetic nanochemistry as well as providing a systematic framework for unifying nanoscience. With further progress, one should anticipate the evolution of future nanoperiodic table(s) suitable for predicting important risk/benefit boundaries in the field of nanoscience

    Entrepreneurial role models, fear of failure, and institutional approval of entrepreneurship: A tale of two regions

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    Studies on the influence of entrepreneurial role models (peers) on the decision to start a firm ar-gue that entrepreneurial role models in the local environment (1) provide opportunities to learn about entrepreneurial tasks and capabilities, and (2) signal that entrepreneurship is a favorable career option thereby reducing uncertainty that potential entrepreneurs face. However, these studies remain silent about the role of institutional context for these mechanisms. Applying an ex-tended sender-receiver model, we hypothesize that observing entrepreneurs reduces fear of fail-ure in others in environments where approval of entrepreneurship is high while this effect is signif-icantly weaker in low approval environments. Taking advantage of the natural experiment from recent German history and using data from the Global Entrepreneurship Monitor Project (GEM), we find considerable support for our hypotheses
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