Perpustakaan Digital

The deployment of distributed renewable energy resources (DRERs) has accelerated globally due to environmental concerns and an increasing demand for electricity. DRERs are considered to be solutions to some of the current challenges related to power grids, such as reliability, resilience, efficiency, and flexibility. However, there are still several technical and non-technical challenges regarding the deployment of distributed renewable energy resources. Technical concerns associated with the integration and control of DRERs include, but are not limited, to optimal sizing and placement, optimal operation in grid-connected and islanded modes, as well as the impact of these resources on power quality, power system security, stability, and protection systems. On the other hand, non-technical challenges can be classified into three categories—regulatory issues, social issues, and economic issues. This Special Issue will address all aspects related to the integration and control of distr

Thin films are important in many of the technologies used every day, impacting major markets for energy, medicine, and coatings. Scientists and engineers have been producing thin films on a wide range of surfaces for many decades but now have begun to explore giving these films new and controlled structures at the nanometer scale. These efforts are part of the new horizons opened by the field of nanoscience and impart novel structures and properties to these thin films. This book covers some of the methods for making these nanostructured thin films and their applications in areas impacting on health and energy usage. Related Books Advances of Nanoparticles and Thin Films Chemistry & Materials Science ... Design and Development of Nanostructured Thin Films Chemistry & Materials Science Nanostructured Surfaces and Thin Films Synthesis by Physical Vapor Deposition Computer Science & Mathematics ... Advances in Functional Thin Films Chemistry & Materials Science ... Synthesis and Modifica

More than 60 years since Artificial Intelligence (AI) technologies and approaches were initially envisaged, it is safe to say that in the last 4-5 years, we have, in practical terms, finally entered the era of AI. As the advanced capabilities of generative Artificial Intelligence (GenAI) and large language models (LLMs) impact varied academic and industrial sectors, this Special Issue Reprint, "Artificial Intelligence in Participatory Environments: Technologies, Ethics and Literacy Aspects", offers a critical framework for understanding the new evolving landscape in this field. Focusing on participatory environments, these nineteen multidisciplinary studies explore how applications based on machine learning (ML) and natural language processing (NLP) reshape workflows and facilitate shifts in living, learning and working. Beyond these significant benefits, the Special Issue highlights emerging challenges and threats that require precise and responsible approaches. Issues of transparency, fairness, accuracy, and data privacy necessitate the development of resilient regulatory and ethical frameworks. To ensure the trustworthy implementation of AI tools and systems, it is essential to prioritize literacy for all involved actors, empowering developers, practitioners, and end-users to achieve the necessary balance between rapid technological evolution and human oversight.

The world has witnessed a rapid development of unmanned systems, which has created fruitful innovative approaches to previously unsolvable problems in Marine and Ocean Engineering. Advanced and intelligent operation methods for marine vehicles are being applied to a variety of significant engineering applications, contributing to the joy of interdisciplinary cooperation. This Reprint focuses on research related to the operation of autonomous marine vehicles, which discusses perception, decision-making, control, and other topics of single/multiple marine vehicles.

The following Special Issue focuses on all of the above classes of materials and the areas of physical metallurgy, process metallurgy, materials science, and processing techniques. Specific areas of interest also include titanium/nickel-based superalloys, intermetallics, advanced metallic materials, nanomaterials, metal matrix composites, functional materials, related synthesis and processing techniques, finite element modeling, statistical analysis, physical/mechanical property characterization, experimental validation, and other relevant phenomena. Physical metallurgy is important in the design and optimization of advanced materials with superior physical and mechanical properties over their service lives via microstructural modifications and processing techniques. The goal of this Special Issue on the physical metallurgy of metals and alloys is to bring together information on the recent progress, novel technologies, and advanced equipment described in our works on the design and development of advanced metals and alloys and provide guidelines/benchmarks for further research in related areas. Composites, intermetallics, and nanomaterials as well as functional materials will also be included.

Several factors have been identified as interfering with the success, rehabilitation, and fitness of athletes from childhood to adulthood, as well as in para-sport, and special populations, according to research. The performance and health of this population are affected by the relationships between stress, maturation, training load, and recovery. Environmental approaches aim to increase efficiency and physiological adaptations in this sense. In various situations and conditions, however, this stimulus–performance–adaptation relationship varies.As a result, we received contributions related (but not limited) to the following topics: training load monitoring; stress and physiological responses during exercise or sports; recovery process after exercise; changes after stress and/or training load; physiology of training in health and sports performance. Related Books Human Performance and Health in Sport and Exercise Public Health & Healthcare Sports Performance and Health Public Health &

The Covid-19 pandemic is having an undeniable impact on all the statements of society. Regarding teaching and learning activities, most educational institutions suspended in-person instruction and moved to remote learning during the lockdown of March and April 2020. Although nowadays many countries have progressively re-opened their educational systems, blended learning is a common practice aimed to reduce the spread of the Covid-19 disease. This disruption has supposed an unprecedented acceleration to the digitalization of teaching and learning. Teaching professionals have been forced to develop their digital competence in a short amount of time, getting mastery in the management of information, the creation of audiovisual contents, and the use of technology to keep their students connected. This Special Issue presents contributions regarding the adoption of distance learning strategies, experiences, or lessons learned in this domain. Related Books Emergency Remote Teaching during

Landslides are among the most widespread and frequent natural hazards. Landsliding is linked to the combination of geological, geomorphological, and climatic factors in response to trigger mechanisms, mostly represented by heavy rainfall events, seismicity, or human action. Landslides directly and indirectly impact a territory, causing fatalities and huge socio-economic losses. Consequently, to avoid serious consequences and support sustainable territorial planning, there is a clear need of correct land use policies and best practices for long-term risk mitigation and reduction. In this context, geomorphological field activities, satellite remote sensing, landslide susceptibility mapping, and innovative GIS analysis offer effective support for mapping and monitoring landslides’ activity at both the local and regional scales. All landslide types are considered, from rockfalls to debris flows, from slow-moving slides to very rapid rock avalanches. Contributions to this Special Issue re

Exit problems for one-dimensional Lévy processes are easier when jumps only occur in one direction. In the last few years, this intuition became more precise: we know now that a wide variety of identities for exit problems of spectrally-negative Lévy processes may be ergonomically expressed in terms of two q-harmonic functions (or scale functions or positive martingales) W and Z. The proofs typically require not much more than the strong Markov property, which hold, in principle, for the wider class of spectrally-negative strong Markov processes. This has been established already in particular cases, such as random walks, Markov additive processes, Lévy processes with omega-state-dependent killing, and certain Lévy processes with state dependent drift, and seems to be true for general strong Markov processes, subject to technical conditions. However, computing the functions W and Z is still an open problem outside the Lévy and diffusion classes, even for the simplest risk models with

The special issue “A Quantitative Analysis and Interdisciplinary Approach to the Sustainable Development Goals” examines the role of the SDGs as a global framework for addressing challenges such as climate change and inequality, emphasizing the need for a robust scientific approach based on quantitative and interdisciplinary methods. Given the complex and interconnected nature of the SDGs, purely qualitative approaches are insufficient: tools are needed that can capture relationships, synergies, and conflicts between economic, social, and environmental dimensions. Interdisciplinarity is central: only by integrating different disciplines can we understand the complexity of sustainability. The 35 articles in the Special Issue indeed cover a wide variety of topics, confirming the multidisciplinary nature of the field, while highlighting a lack of studies in the medical field. The use of technologies such as big data and artificial intelligence expands analytical possibilities but also introduces challenges related to energy consumption. Finally, the text highlights the need for a pragmatic and participatory approach, in which young people also play an active role. However, the 2030 deadline is rapidly approaching and requires the adoption of a long-term vision capable of looking beyond that date. People must be at the center of the agenda, with technologies that support them rather than replace them, according to a principle of solidarity and fraternity.

Throughout a building’s service life, its structure will inevitably face multiple hazards, such as seismic and wind events. The vulnerability of buildings under the impact of multi-hazards has become a significant issue for the sustainable development of society. This issue can be approached fundamentally by enhancing the resilience of buildings against multi-hazards, e.g., seismic and wind hazards, and updating design approaches. To this end, we launched the Special Issue of Buildings titled “Structural Reliability, Resilience and Design of Buildings against Multi-hazards”. The main aim of this Special Issue, reprinted here, is to explore the recent challenges and developments in the field of reliability assessment, resilience evaluation/enhancement techniques, and structural design theories for individual building structures and clusters under multiple hazards.

The mining and minerals industry has witnessed a significant increase in the generation of solid waste (e.g., mine tailings, coal gangue, coal fly ash, slag) as the industry has evolved. Due to the substantial potential for environmental harm, the management of solid waste remains one of the most challenging issues facing the industry. The traditional methods employed in solid waste disposal, such as direct surface disposal, have numerous limitations, hindering their broader application. These limitations include the risk of storage facility failure, the use of land resources, and the potential for heavy metal contamination. Consequently, there is a pressing need for innovative strategies that minimize the generation of solid waste in the mining and minerals sector. Research efforts have aimed to enhance approaches to the minimization of waste minimization across various dimensions. While some studies focus on reducing the generation of waste at the source, others emphasize the development of novel recycling methods. This reprint highlights research related to the minimization of solid waste within the mining and minerals industry. It includes experimental investigations and machine learning-based predictive models that address various topics, such as the recovery of valuable components from copper slag, the recycling of solid waste and its use as a supplementary cementitious material, the reuse of solid waste in backfill applications, and the employment of advanced machine learning techniques to support waste minimization efforts.

The collection on “Public Health Palliative Care (PHPC) and Public Palliative Care Education (PPCE)” highlights recent advances and challenges in PHPC and PPCE. The articles demonstrate the breadth and diversity of local responses from across the globe, including Europe, Asia, Australia and South America. The COVID-19 pandemic clearly shows how collaboration between healthcare services and communities is an essential component of public health. The collection adds to the growing body of knowledge, based on practice, theory and research, about PHPC and PPCE. It is clear that global perspectives of PHPC are best expressed through both international, national and local activities including PPCE, such as Last Aid. Partnerships between healthcare services, civic organisations and communities are essential to increase awareness, skills and practice. It is evident that PHPC and PPCE are needed to improve palliative care support by the public in communities. These examples show that encourag

This reprint compiles the articles, communications, and review articles from top researchers describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles. This reprint encompasses the key topics related to drone design, communications as well as autonomous Flight and Navigation. Special attention is paid to the drones’ applications to environmental and earth sciences, including in agriculture, forestry, water, and marine environments; other innovative applications are also explored including in relation to the field of application, such as the inclusion of new deep learning techniques. Related Books Feature Papers of Drones Volume I Environmental & Earth Sciences ... Innovative Technologies and Services for Unmanned Aerial Vehicles Computer Science & Mathematics Design, Simulation and New Applications of Unmanned Aerial Vehicles Computer Science & Mathematics ... Design, Simulation and New Applications of Unmanned Aerial Vehicles Computer Scie

Ants are a ubiquitous, highly diverse, and ecologically dominant faunal group. They represent a large proportion of global terrestrial faunal biomass and play key ecological roles as soil engineers, predators, and re-cyclers of nutrients. They have particularly important interactions with plants as defenders against herbivores, as seed dispersers, and as seed predators. One downside to the ecological importance of ants is that they feature on the list of the world’s worst invasive species. Ants have also been important for science as model organisms for studies of diversity, biogeography, and community ecology. Despite such importance, ants remain remarkably understudied. A large proportion of species are undescribed, the biogeographic histories of most taxa remain poorly known, and we have a limited understanding of spatial patterns of diversity and composition, along with the processes driving them. The papers in this Special Issue collectively address many of the most pressing qu

This book contains original peer-reviewed articles written by some of the most prominent international physicists active in the field of hydrodynamics. The topic is entirely devoted to the study of the transitional regimes of incompressible viscous flow found at the onset of turbulent flows. Nine articles written for this 2020 Special Issue of the journal Entropy (MDPI) have been gathered at the crossroads of fluid mechanics, statistical physics, complexity theory, and applied mathematics. They include experimental, analytic, and computational material of an academic level that has not been published anywhere else. Related Books Intermittency and Self-Organisation in Turbulence and Statistical Mechanics Computer Science & Mathematics Thermal Flows Engineering Turbulence and Flow–Sediment Interactions in Open-Channel Flows Environmental & Earth Sciences ... Recent Advances in Fluid Mechanics: Feature Papers, 2022 Computer Science & Mathematics ... Modelling Flows in Pipes and Channels

In recent years, deep learning techniques have been widely used in medical image analysis. These techniques employ deep neural networks to automatically extract multi-level, multi-scale, abundant information (features) from image data, which is hard to achieve with conventional machine learning techniques, which use hand-crafted feature parameters, including supervised learning (with task-driven models), unsupervised or generative learning (with data-driven models), semi-supervised learning (with hybrid task-driven and data-driven models), reinforcement learning (with environment-driven models), and physics-informed learning (hybrid task-driven and physics-driven models). The vast applications of deep learning techniques in medical image analysis cover lesion detection and segmentation, disease diagnosis, treatment monitoring, efficacy evaluation, prognostic prediction, and even biomechanical analysis. In addition to medical image post-processing, deep learning techniques can also be applied to the front-end (e.g., image reconstruction) to enhance the quality of medical imaging. Given the high level of research interest and clinical application prospects, deep learning techniques have continued to develop, especially in the field of medical image analysis. This Reprint aims to report on state-of-the-art deep learning techniques applied to medical image analysis.

This reprint comprises a collection of 10 articles previously published in 2023 and 2024 to form a Special Issue of the journal Youth on “Residential Care for Children and Young people”. The Special Issue was conceived to explore both conceptual and practice issues in relation to care experience and alternative group care for children and youth.

Obstructive sleep apnea (OSA) is a common disorder with strong associations with cardiovascular, cerebrovascular, metabolic, and cognitive consequences. Continuous Positive Airway Pressure (CPAP) treatment is the first-line therapy for adults with OSA who are symptomatic. However, many individuals with comorbidities do not report symptoms associated with OSA, and adherence to CPAP is poor, especially in individuals with the non-sleepy OSA phenotype. This reprint contains further updates on the current perspectives on the treatment of OSA in order to highlight multidisciplinary approaches, personalized treatment strategies, and identification of the predictors of response to treatment, both in the general population and in clinical cohorts. Reviews regarding the present and future of physiological traits and the use of telemedicine and machine learning are of particular interest.

This reprint contains 15 articles from the Special Issue of the MDPI journal Processes on "Machine Learning-Assisted Intelligent Processing and Optimization of Complex Systems". These articles focus on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling.Focusing on the abovementioned subjects, this reprint can be useful for researchers interested in intelligent optimization techniques and their applications in the fields of artificial intelligence and machine learning. We believe that this reprint will encourage the convergence between many communities. Related Books Computational Intelligence and Machine Learning Computer Science & Math

This reprint compiles the articles, communications, and review articles from top researchers describing novel or new cutting-edge designs, developments, and/or applications of unmanned vehicles. This reprint encompasses the key topics related to drone design, communications as well as autonomous Flight and Navigation. Special attention is paid to the drones’ applications to environmental and earth sciences, including in agriculture, forestry, water, and marine environments; other innovative applications are also explored including in relation to the field of application, such as the inclusion of new deep learning techniques. Related Books Feature Papers of Drones Volume II Environmental & Earth Sciences ... Innovative Technologies and Services for Unmanned Aerial Vehicles Computer Science & Mathematics Design, Simulation and New Applications of Unmanned Aerial Vehicles Computer Science & Mathematics ... Design, Simulation and New Applications of Unmanned Aerial Vehicles Computer Sci

This Special Issue highlights the most recent research being carried out in the field of NLP methods to face these open issues, with particular emphasis on emerging approaches for learning interactively or autonomously from data, single and multiple language understanding and grounding for analysis and generation, as well as potential or real applications in different domains and everyday devices. Related Books Natural Language Processing: Emerging Neural Approaches and Applications Computer Science & Mathematics Current Approaches and Applications in Natural Language Processing Engineering Recent Applications of Machine Learning in Natural Language Processing (NLP) Computer Science & Mathematics ... Computational Linguistics and Natural Language Processing Social Sciences, Arts & Humanities ... Natural Language Processing (NLP) and Machine Learning (ML)—Theory and Applications Computer Science & Mathematics The recommendations have been generated using an AI system. About: About

The book entitled “Biodiversity of Marine Microbes” aims at highlighting the significance of marine microbes as primary producers, their contribution in complex ecological processes and their roles in biogeochemical cycles and ecosystem functioning. The book includes five research papers covering the diversity and composition of marine microbial communities representing all three domains of life in various marine environments, including coastal eutrophic areas, ice waters, and lagoons. One paper examines the diversity and succession of bacterial and archaeal communities from coastal waters in mesocosm experiments. The combination of classical tools with novel technological advances implemented in the methods of the papers offered an opportunity to answer fundamental questions and shed light on the complex and diverse life of marine microbes. Related Books Marine Microbial Diversity as a Source of Bioactive Natural Products Biology & Life Sciences ... Marine Microbial Diversity as Sour

The study of causality examines the relations and regularities found in a given environment that are stronger than merely probabilistic relations, in the sense that a causal relation allows for evaluating a change in the consequence given a change in the cause. Causation is crucial not only for predictive accuracy but also for control, explanation, and intervention. Causality is central to much of the scientific enterprise—and even everyday life—and there has been increasing interest in recent decades in causal modeling, inference, and reasoning. Causal models enable us to perform other types of reasoning that are not possible with associative models: (i) interventions, where we want to find the effects of an external agent forcing a variable to a specific value (in contrast with merely observing that variable’s value); and (ii) counterfactuals, where we want to reason about what would have happened if certain information had been different from what actually happened. Causality usually cannot be directly observed, and so a long-standing goal of causality researchers has been causal discovery: inferring the underlying causal model from observational data. Multiple causal discovery methods have been developed and successfully applied in different fields, such as biology, medicine, and economics, among others. This Special Issue presents recent advances in causal reasoning and causal discovery based on causal graphical models, including novel applications in different domains. It includes contributions from theory to applications in the following aspects: theory, causal reasoning, causal discovery, and applications.