This reprint gathers 16 contributions (13 research articles and 3 reviews) covering different areas of analytical chemistry. Many of these contributions deal with the development and application in real matrices of chromatographic methods interfaced with mass spectrometry, but also spectroscopic, electrochemical, and separation methods are also proposed.

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This Topical Collection of Molecules provides the most recent advancements and trends within the framework of food analysis, confirming the growing public, academic, and industrial interest in this field. The articles broach topics related to sample preparation, separation science, spectroscopic techniques, sensors and biosensors, as well as investigations dealing with the characterization of macronutrients, micronutrients, and other biomolecules. It offers the latest updates regarding alternative food sources (e.g., algae), functional foods, effects of processing, chiral or achiral bioactive compounds, contaminants, and every topic related to food science that is appealing to readers. Nowadays, the increasing awareness of the close relation among diet, health, and social development is stimulating demands for high levels of quality and safety in agro-food production, as well as new studies to fill gaps in the actual body of knowledge about food composition. For these reasons, modern research in food science and human nutrition is moving from classical methodologies to advanced instrumental platforms for comprehensive characterization. Nondestructive spectroscopic and imaging technologies are also proposed for food process monitoring and quality control in real time.

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As faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present their novel computational methods that have engineering and physics applications.

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The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications. We publish papers from all areas of mathematics and engineering, and especially those that showcase novel machine learning techniques that leverage subject matter expertise. We aim to foster the communication of the latest research results in the areas of applied and computational mathematics.

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Liquid biopsy shows promise for cancer screening and diagnostics. This reprint collects recent scientific literature on the identification and application of tumor biomarkers in biological fluids to improve the diagnosis of cancer and the identification of optimal therapeutic strategies.

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On 11 March 2020, the World Health Organisation declared novel coronavirus (SARS-CoV-2) an unprecedented global pandemic. Nearly every country across the globe is struggling to reduce the spread of the COVID-19 virus and to limit its health, societal and economic consequences. As a response to that, with almost immediate effect, students, teachers and workers in general and across the globe were thrown into a new scenario of online work and education. In the midst of this emotional climate laden with fear, uncertainty, sadness and anxiety, millions of students all over the world were confined to their homes and the entire educational community had to adapt to a distance education model. The same occured with workers of different disciplines; they have to balance work and life in the same place. Therefore, homes suddenly became schools, universities and workplaces all at the same time. Against this backdrop, this Special Issue focuses on the study, evaluation and analysis of the opportunities the pandemic offers in three related aspects: first, for building an education for sustainable development. Second, for creating decent working conditions. Finally, to enhance health and well-being both at the workplace and at home. Authors from a range of disciplines, such as education, psychology, management, social sciences and other areas related to sustainable development, have contributed with differrent manuscripts. They address the challenges of studying, working and living in times of uncertainty in order to build sustainable development in those areas from theoretical and applied research.

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This Special Issue explores the fascinating topic of urban heat islands (UHIs), examining them from temporal and spatial perspectives. We embark on a journey that focuses on the essential impacts of UHI formations, including land use composition, city characteristics, and anthropogenic factors. Our objective is to raise awareness of the many facets of UHIs and their significant effects on urban environments and sustainability. This collective aim is to further strengthen urban sustainability through a deeper understanding of UHI dynamics. This volume includes a wide range of topics related to UHIs, including cutting-edge methods and datasets for capturing UHI phenomena. We investigate the spatial interactions between UHI intensity and land use/cover distribution within metropolitan areas, examine the geographic patterns and processes underlying UHIs in sprawling cities, and analyze the spatial differences in UHI intensity between developing and developed countries. Additionally, we focus on UHI catastrophe mitigation and adaptation measures, which are crucial for setting sail for a sustainable urban future. Finally, we engage in the critical work of prediction and scenario analysis, equipping policymakers and urban planners with the insights necessary for informed decision-making. We express our thanks to the researchers, academics, and contributors who have made this Special Issue possible as we begin this investigation into urban heat islands. We aim to foster a comprehensive understanding of UHIs and contribute to the broader discourse on urban sustainability.

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"Health and Public Health Applications for Decision Support Using Machine Learning" is a reprint that explores the intersection of machine learning and health sciences. It presents a collection of research and innovations showcasing how data-driven algorithms can transform patient care, disease diagnosis, and public health management. The reprint covers a wide range of topics, including natural language processing for biomedical relation extraction, ensemble learning for blood glucose level forecasting in diabetes management, machine learning for predicting walking stability and fall risk among the elderly, deep learning for pneumonia-infected lung volume quantification, and more.The reprint also discusses applications in precision medicine, early detection of renal damage, cardiac health monitoring, stress classification for mental health assessment, and early diagnosis of intracranial internal carotid artery stenosis. It emphasizes the role of machine learning in managing health crises, such as COVID-19 detection using ECG, voice, and X-ray systems, and reviews AI models in diagnosing adult-onset dementia disorders.Overall, this reprint aims to inspire researchers and healthcare professionals by showcasing the transformative potential of machine learning in healthcare. It hopes to encourage further research and collaboration to advance healthcare and technological innovations for a healthier future.

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Authenticity and traceability are crucial in order to overcome frauds in the international food trade. Control measures are perceived as the greatest vulnerability in the food supply chain. In order to decrease contribution to the overall perceived fraud vulnerability, analytical approaches and chemometrics are usually employed.

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Microgrids are a growing segment of the energy industry, representing a paradigm shift from centralized structures toward more localized, autonomous, dynamic, and bi-directional energy networks, especially in cities and communities. The ability to isolate from the larger grid makes microgrids resilient, while their capability of forming scalable energy clusters permits the delivery of services that make the grid more sustainable and competitive. Through an optimal design and management process, microgrids could also provide efficient, low-cost, clean energy and help to improve the operation and stability of regional energy systems. This book covers these promising and dynamic areas of research and development and gathers contributions on different aspects of microgrids in an aim to impart higher degrees of sustainability and resilience to energy systems.

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Modelling and simulation in acoustics is currently gaining importance. In fact, with the development and improvement of innovative computational techniques and with the growing need for predictive models, an impressive boost has been observed in several research and application areas, such as noise control, indoor acoustics, and industrial applications. This led us to the proposal of a special issue about “Modelling, Simulation and Data Analysis in Acoustical Problems”, as we believe in the importance of these topics in modern acoustics’ studies. In total, 81 papers were submitted and 33 of them were published, with an acceptance rate of 37.5%. According to the number of papers submitted, it can be affirmed that this is a trending topic in the scientific and academic community and this special issue will try to provide a future reference for the research that will be developed in coming years.

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In recent decades, remote sensing technology has been incorporated in numerous mineral exploration projects in metallogenic provinces around the world. Multispectral and hyperspectral sensors play a significant role in affording unique data for mineral exploration and environmental hazard monitoring. This book covers the advances of remote sensing data processing algorithms in mineral exploration, and the technology can be used in monitoring and decision-making in relation to environmental mining hazard. This book presents state-of-the-art approaches on recent remote sensing and GIS-based mineral prospectivity modeling, offering excellent information to professional earth scientists, researchers, mineral exploration communities and mining companies.

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This reprint exists to solve high complexity issues in remote sensing data processing, geochemical data analysis, geophysical data analysis and appropriate applications of GIS techniques for data fusion designed for mineral and hydrocarbon exploration. This reprint contains updated and informative knowledge of remote sensing imagery, geochemistry, geophysics and geospatial techniques that can assist in delineating the signatures and patterns linked to deep-seated, covered, blind, or buried mineral deposits and onshore oil slick detection, offshore oil spill monitoring and hydrocarbon exploration. It includes several color figures for remotely-sensed recognition of mineralization-related footprints. Additionally, this reprint comprehends several interactive flowcharts for describing the procedures explained therein.

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Plant bioactive compounds are essential for human health due to their multiple biological effects, such as antioxidant, anticarcinogenic, antiallergenic, anti-inflammatory, antimutagenic, and antimicrobial activities leading to beneficial effects on various non-communicable diseases, such as autoimmune, inflammatory, cardiovascular, cancer, metabolic, and neurodegenerative diseases. Identifying these components, as well as establishing their beneficial health effects, will contribute to the discovery of therapeutics for the prevention and treatment of various disorders. Additionally, the screening of natural sources for novel biologically active metabolites is an essential part of several drug discovery programs.This Special Issue aims to present recent developments in high-throughput and efficient analytical approaches enabling the identification of plant-based compounds, the establishment of new protocols for the evaluation of bioactivities, and methods for the extraction, isolation, and structural characterization of new bioactive components with nutraceutical and therapeutic potential.

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The great potential of remote sensing technologies for operational use in sustainable forest management is addressed in this book, which is the reprint of papers published in the Remote Sensing Special Issue “Operationalization of Remote Sensing Solutions for Sustainable Forest Management”. The studies come from three continents and cover multiple remote sensing systems (including terrestrial mobile laser scanning, unmanned aerial vehicles, airborne laser scanning, and satellite data acquisition) and a diversity of data processing algorithms, with a focus on machine learning approaches. The focus of the studies ranges from identification and characterization of individual trees to deriving national- or even continental-level forest attributes and maps. There are studies carefully describing exercises on the case study level, and there are also studies introducing new methodologies for transdisciplinary remote sensing applications. Even though most of the authors look forward to continuing their research, nearly all studies introduced are ready for operational use or have already been implemented in practical forestry.

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Both vegetables and fruits, as plant-based foods, are known for their abundance of bioactive compounds, which play a crucial role in disease prevention. Researchers from various disciplines have dedicated significant efforts to understanding the compositions of these bioactive compounds and exploring how fruits and vegetables contribute to promoting health and preventing diseases. This reprint presents studies on the composition of bioactive compounds found in the main fruit and vegetable species, their health effects when consumed fresh or processed, and their mechanisms of action against human diseases, including in vitro and in vivo models.

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The purpose of this reprint is to present current research on the use of plant tissue cultures to produce specialized metabolites or secondary metabolites in plants. Numerous review articles on the use of instrument engineering, data modeling, and metabolic regulation in the synthesis of industrially significant plant secondary metabolites are included in this Special Issue. Research has covered contemporary methodologies like elicitation and the use of different bioreactors for biomass and metabolite syntheses. The research article addresses the production of specific metabolites employing cells, adventitious roots, and shoot cultures. Experts in the field provide their perspectives on research findings and future directions in this reprint. For those working in the fields of plant biotechnology, food, pharmaceuticals, and nutraceutical science, as well as for those working in academics, industry, and policymaking and students, the review and research papers will be helpful.

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“Smart Sensing Technologies for Agriculture” is a Special Issue of Sensors that includes 14 research papers on diverse topics about the measurement of physical, chemical, and biological characteristics of soil, plants, and animals related to modern farming practices.

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This book covers the most recent research activities and achievements regarding to the solid phase microextraction (SPME) technique. It is a powerful sample preparation tool that addresses the new challenges of analytical laboratories. Among others, its fundamental applications involved the sampling of volatile compounds from various matrixes. The demonstrated topics ranged from aroma characterization of various fruits, essential oils to the utilization of SPME for in-tube extraction and isolation of selected compounds from complex samples followed by state-of-the-art analytical techniques.

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