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    19683 research outputs found

    Advances in point-of-care and molecular techniques to detect waterborne pathogens

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    Abstract: Rapid and precise detection of waterborne pathogens is critical for effective public health management and environmental safety. Traditional methods for water quality monitoring, considered the “Gold Standard,” are time-consuming, costly, and rely on centralized laboratories and expertise. These methods are impractical for on-site, real-time monitoring, and requiring further improvements. This review explores various waterborne pathogens and cutting-edge molecular detection techniques. It highlights the growing importance of point-of-care and point-of-application methods to expedite results and improve health risk management. Loop-mediated isothermal amplification emerges as a reliable, rapid, and accessible tool in the realms of on-site diagnostics and surveillance. Moreover, the review emphasizes the crucial role of water sample preparation and in-field nucleic acid isolation in augmenting pathogen detection to enable precise assessments of water quality. The advancement of these techniques will guarantee access to safe water and improve the management of waterborne diseases.</p

    50 years of Resources Policy: A bibliometric analysis

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    Resources Policy is a leading international journal in the field of economics and policy issues related to mineral and fossil fuel extraction, production, and use. The journal was created in 1974 and in 2024 celebrates its 50th anniversary. Motivated by this special event, this paper presents a bibliometric overview of the leading trends of the journal during its first half-century of existence. This paper analyses Resources Policy's publication and citation structure using the Web of Science Core Collection and examines various aspects, including the most cited documents, productive authors, institutions, countries, and popular keywords, and topics. The paper also develops a graphical visualization of the bibliographic data using the Visualization of Similarities (VOS) viewer software. This approach utilises various bibliometric techniques, including bibliographic coupling, co-citation, and co-occurrence of keywords. The results demonstrate a significant expansion of the journal over the past five years and highlight its global profile, with publications from around the world. Currently, Chinese researchers are the most productive, due to a significant increase in their contributions over the last five years

    Data set for a comprehensive tutorial on the SOM-RPM toolbox for MATLAB

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    This data set is uploaded as supporting information for the publication entitled:A Comprehensive Tutorial on the SOM-RPM Toolbox for MATLABThe attached file 'case_study' includes the following:X : Data from a ToF-SIMS hyperspectral image. A stage raster containing 960 x800 pixels with 963 associated m/z peaks.pk_lbls: The m/z label for each of the 963 m/z peaks.mdl and mdl_masked: SOM-RPM models created using the SOM-RPM tutorial provided within the cited article.Additional details about the datasets can be found in the published article.V2 - contains modified peak lists to show intensity weighted m/z rather than peak midpoint. If you use this data set in your work, please cite our work as follows:[LINK TO BE ADDED TO PAPER ONCE DOI RECEIVED]</p

    Mastering Death: The Roles of Viral Bcl-2 in dsDNA Viruses

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    Proteins of the Bcl-2 family regulate cellular fate via multiple mechanisms including apoptosis, autophagy, senescence, metabolism, inflammation, redox homeostasis, and calcium flux. There are several regulated cell death (RCD) pathways, including apoptosis and autophagy, that use distinct molecular mechanisms to elicit the death response. However, the same proteins/genes may be deployed in multiple biochemical pathways. In apoptosis, Bcl-2 proteins control the integrity of the mitochondrial outer membrane (MOM) by regulating the formation of pores in the MOM and apoptotic cell death. A number of prosurvival genes populate the genomes of viruses including those of the pro-survival Bcl-2 family. Viral Bcl-2 proteins are sequence and structural homologs of their cellular counterparts and interact with cellular proteins in apoptotic and autophagic pathways, potentially allowing them to modulate these pathways and determine cellular fate

    Theoretical Studies of Anisotropic Melting of Ice Induced by Ultrafast Nonthermal Heating

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    Water and ice are routinely studied with X-rays to reveal their diverse structures and anomalous properties. We employ a hybrid collisional-radiative/molecular-dynamics method to explore how femtosecond X-ray pulses interact with hexagonal ice. We find that ice makes a phase transition into a crystalline plasma where its initial structure is maintained up to tens of femtoseconds. The ultrafast melting process occurs anisotropically, where different geometric configurations of the structure melt on different time scales. The transient state and anisotropic melting of crystals can be captured by X-ray diffraction, which impacts any study of crystalline structures probed by femtosecond X-ray lasers

    Qualifying public perceptions of art therapy: A mixed methods study of community discussion forums

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    This study explores public perspectives on art therapy, a vibrant and evolving field, revealing exciting opportunities to reshape misconceptions held by the public and healthcare professionals. It spotlights the use of social media as a communicative tool to collect authentic feedback on health services. The surge in social media usage opens new doors for capturing spontaneous, real-world opinions, with platforms like Quora and Reddit offering a treasure trove of data. Using a mixed-methods approach, the study examines online conversations about art therapy, employing precise content and thematic analyses with In Vivo coding. It identified ten themes across five key areas including efficacy, outcomes, applications, purpose, and professionalism. Significantly, the findings illuminate a rising tide of positive perceptions around art therapy methods and goals, with a trend of increasingly favourable views emerging over the last five years, showcasing the growing impact and acceptance of the field.</p

    A cloud-based architecture for explainable Big Data analytics using self-structuring Artificial Intelligence

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    Big Data is steadily expanding beyond the boundaries of its foundational constructs of three primary Vs, Volume, Velocity and Variety, and two secondary Vs, Veracity and Value. The advent of 5G networks, Edge computing and IoT technologies has transformed Big Data into this modern context. With these new manifestations of Big Data, the focus is not only on the data itself but on the context that it applies to its immediate environment as well as the human and societal perception of this context. It is increasingly challenging for conventional AI algorithms to process and transform this data, analyse and visualise a broad spectrum of insights, and then formulate the explainability of such insights in terms of bias, transparency, safety, ethics, and causality. Self-structuring Artificial Intelligence (SSAI) addresses the limitations of conventional AI by adapting to the inherent structure of the data, incrementally learning and abstracting from this structure. SSAI has not been investigated in a cloud-based setting for generating explainable insights from these new types of Big Data. In this paper we propose a cloud-based architecture for explainable Big Data analytics using SSAI in highly-connected 5G and Edge computing environments. The proposed architecture is empirically evaluated on a commercial scale Big Data use case of Smart Grid for Smart Cities. The results of these experiments confirm the functionality and effectiveness of the proposed architecture

    Design of Complex Nanostructures Based on Metallosupramolecular Assembly

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    Submitted in total fulfillment of the requirements for the degree Doctor of Philosophy to the School of Agriculture, Biomedicine and Environment, La Trobe University, Victoria, Australia.</p

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