69 research outputs found

    Veterinary Microbiology & Parasitology

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    Numerous pathogens affect animal health and wellbeing and production efficiency. These pathogens also have a considerable impact on social economics, food safety and security, and human health. Infectious diseases that originate from both domesticated animals and wildlife represent one of the greatest threats to human health. Recent studies show that domesticated species harbor approximately 84 times more zoonotic viruses than wild species. Eight of the top 10 mammalian species with the highest number of zoonotic viruses are domestic, such as pigs, cattle, and horses. Many animal parasites are also zoonotic, constituting an additional burden on human health. Furthermore, the rapid emergence and spread of drug-resistant pathogen strains pose new threats to animal and human health. Climate changes will undoubtedly alter the interactions between animals and between animals and humans, which will have a huge impact on the transmission rate of existing pathogens and the emergence of new pathogens or the reemergence of old pathogens. In this special collection, interactions of all major pathogen types, including viruses, bacteria, mites and flies, protozoans, and helminths, and their hosts, such as wild and companion animals and livestock species, are discussed. Further, anthelmintic activities of natural products are evaluated. The relevance and utility of cutting-edge tools, such as immunology, genomics and genetics, microbiome studies and metabolomics, and molecular epidemiology, in dissecting host-pathogen interactions are also discussed. This special collection provides a broad knowledge base that encourages dialogue across a wide distribution of the research community in veterinary microbiology and parasitology

    Sustainable Smart Cities and Smart Villages Research

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    ca. 200 words; this text will present the book in all promotional forms (e.g. flyers). Please describe the book in straightforward and consumer-friendly terms. [There is ever more research on smart cities and new interdisciplinary approaches proposed on the study of smart cities. At the same time, problems pertinent to communities inhabiting rural areas are being addressed, as part of discussions in contigious fields of research, be it environmental studies, sociology, or agriculture. Even if rural areas and countryside communities have previously been a subject of concern for robust policy frameworks, such as the European Union’s Cohesion Policy and Common Agricultural Policy Arguably, the concept of ‘the village’ has been largely absent in the debate. As a result, when advances in sophisticated information and communication technology (ICT) led to the emergence of a rich body of research on smart cities, the application and usability of ICT in the context of a village has remained underdiscussed in the literature. Against this backdrop, this volume delivers on four objectives. It delineates the conceptual boundaries of the concept of ‘smart village’. It highlights in which ways ‘smart village’ is distinct from ‘smart city’. It examines in which ways smart cities research can enrich smart villages research. It sheds light on the smart village research agenda as it unfolds in European and global contexts.

    Mathematical analysis for tumor growth model of ordinary differential equations

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    Special functions occur quite frequently in mathematical analysis and lend itself rather frequently in physical and engineering applications. Among the special functions, gamma function seemed to be widely used. The purpose of this thesis is to analyse the various properties of gamma function and use these properties and its definition to derive and tackle some integration problem which occur quite frequently in applications. It should be noted that if elementary techniques such as substitution and integration by parts were used to tackle most of the integration problems, then we will end up with frustration. Due to this, importance of gamma function cannot be denied

    Volume II: Mining Innovation

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    Contemporary exploitation of natural raw materials by borehole, opencast, underground, seabed, and anthropogenic deposits is closely related to, among others, geomechanics, automation, computer science, and numerical methods. More and more often, individual fields of science coexist and complement each other, contributing to lowering exploitation costs, increasing production, and reduction of the time needed to prepare and exploit the deposit. The continuous development of national economies is related to the increasing demand for energy, metal, rock, and chemical resources. Very often, exploitation is carried out in complex geological and mining conditions, which are accompanied by natural hazards such as rock bursts, methane, coal dust explosion, spontaneous combustion, water, gas, and temperature. In order to conduct a safe and economically justified operation, modern construction materials are being used more and more often in mining to support excavations, both under static and dynamic loads. The individual production stages are supported by specialized computer programs for cutting the deposit as well as for modeling the behavior of the rock mass after excavation in it. Currently, the automation and monitoring of the mining works play a very important role, which will significantly contribute to the improvement of safety conditions. In this Special Issue of Energies, we focus on innovative laboratory, numerical, and industrial research that has a positive impact on the development of safety and exploitation in mining

    Women in Artificial intelligence (AI)

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    This Special Issue, entitled "Women in Artificial Intelligence" includes 17 papers from leading women scientists. The papers cover a broad scope of research areas within Artificial Intelligence, including machine learning, perception, reasoning or planning, among others. The papers have applications to relevant fields, such as human health, finance, or education. It is worth noting that the Issue includes three papers that deal with different aspects of gender bias in Artificial Intelligence. All the papers have a woman as the first author. We can proudly say that these women are from countries worldwide, such as France, Czech Republic, United Kingdom, Australia, Bangladesh, Yemen, Romania, India, Cuba, Bangladesh and Spain. In conclusion, apart from its intrinsic scientific value as a Special Issue, combining interesting research works, this Special Issue intends to increase the invisibility of women in AI, showing where they are, what they do, and how they contribute to developments in Artificial Intelligence from their different places, positions, research branches and application fields. We planned to issue this book on the on Ada Lovelace Day (11/10/2022), a date internationally dedicated to the first computer programmer, a woman who had to fight the gender difficulties of her times, in the XIX century. We also thank the publisher for making this possible, thus allowing for this book to become a part of the international activities dedicated to celebrating the value of women in ICT all over the world. With this book, we want to pay homage to all the women that contributed over the years to the field of AI

    Intelligent Sensors for Human Motion Analysis

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    The book, "Intelligent Sensors for Human Motion Analysis," contains 17 articles published in the Special Issue of the Sensors journal. These articles deal with many aspects related to the analysis of human movement. New techniques and methods for pose estimation, gait recognition, and fall detection have been proposed and verified. Some of them will trigger further research, and some may become the backbone of commercial systems

    Effects of land management upon species population dynamics: a spatially explicit, individual-based model

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    Individual-based approaches in ecology provide a new approach to spatially explicit modelling. They are paralleled by the emergence of agent-based modelling in the field of artificial intelligence (AI) that is manifest in object-based approaches in a number of geographical disciplines, from hydrology to sociology. An individual-based approach to the simulation of organisms in a spatial context allows for a greater understanding of how individual-level behaviour and interactions result in population-level phenomena at the landscape-scale. Such models are inherently flexible and adaptable to other species or systems, and the model can be parameterised from biological behavioural information widely available in the literature. This research constructs, analyses and experiments with an individual-based model of aphid (Rhopalosiphum padi) population dynamics in agricultural landscapes during the autumn and winter. The model combines deterministic equations governing the development of the aphids with stochastic, behavioural rules. Several stages of model assessment validate the model: assessment at the conceptual, developmental and operational stages. The need for a solution for the model to cope with large population sizes led to experimentation with both mathematical and computational solutions to this problem. It was found that parallel computing to distribute the simulation across a 30-node Beowulf cluster was the most effective at increasing model efficiency whilst preserving model behaviour. Key scenarios are presented, that show the power of this approach in predicting potential impacts of agricultural landscape change, including the effects of crop management, marginal habitat configuration and pesticide regime. This research clearly demonstrates the potential of spatially explicit individual-based modelling to predict scenarios that may advise policy decision-makers as a landscape management tool

    The respiratory microbiota of preterm infants at risk of chronic lung disease of prematurity

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    Extreme preterm infants are at risk of developing chronic lung disease of prematurity (CLD). This thesis examines the bacterial colonisation of the respiratory tract in extreme preterm infants. Longitudinal sampling was performed from three anatomical sites within the respiratory tract of preterm infants over the first 28 days of life (Nasopharyngeal aspirates (NPA), tracheal aspirates (TA) and bronchoalveolar lavages (BAL)). Sequencing the bacterial 16S rRNA gene identified bacteria within the samples. IL-6 and IL-8 concentrations were measured using ELISA on TA and BAL samples. Widespread antibiotic use appeared to suppress bacterial load at all sites with most samples appearing sterile. Most samples successfully sequenced showed a dominant bacterial genus, consistent with previous studies of neonatal bacterial colonisation. In all samples, organisms from the Proteobacteria and Firmicutes phyla were most abundant with smaller number of Tenericutes and Actinobacteria. NPA samples demonstrated a clear effect of delivery mode over early colonisation patterns and a progression from Firmicutes to Proteobacteria dominated profiles over time. Tracheal aspirate samples showed evidence of an infectious process or dysbiosis associated with bacterial colonisation, with higher concentrations of IL-6 and IL-8 in samples successfully sequenced. BALs sampling more distally in the lungs verified these results suggesting pulmonary infection in preterm infants may be more common than clinically suspected. Comparing the three anatomical sites sampled revealed significant differences in bacterial community structure suggesting that these are separate bacterial niches. Also presented is work analysing the effect of extracellular apoptosis-associated speck-like protein containing a caspase activation domain (ASC), a protein involved in the initiation and propagation of the innate immune response. ASC was demonstrated to be present and bioactive in BAL supernatant from preterm infants. ASC induced IL-6 and IL-8 secretion in cell culture models and is a potential therapeutic target for preventing CLD in preterm infants
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