Bücher veröffentlicht von Mdpi AG

The most important class of polymers is block copolymers (BCPs) since they can be prepared through different methods and exhibit various properties combined with chemically different segments. The importance of block copolymers can be supported by the multitude of related manuscripts published daily, their use in practical applications in almost all areas, and novel discoveries based on BCPs in many aspects of life. This Special Issue focuses on various matters from different areas of block copolymer research, showing advances and applications in self-assembly, crystallization, synthesis, chemical modification, 3D printing, membranes, energy materials, nanotechnology, hybrid materials, micelles, order-disorder transition, and biomaterials.

In the last decade, design and material innovations for manufacturing composites have reached new heights. Thermoplastic polymers and their composites have become the most in-demand materials in recent times as they provide numerous advantages over thermoset composites. Thermoplastic polymers have a high damage tolerance, high impact resistance, recyclability, formability, weldability, repairability, and cost-effectiveness compared with thermoset composites. Thermoplastic polymers and composites are widely used in automotive, aerospace, electrical and electronics, industrial, and medical applications. Thermoplastic composites are estimated to grow from USD 28.0 billion in 2019 to USD 36.0 billion by 2024. High-performance thermoplastic materials are used in conjunction with a multitude of manufacturing processes like injection moulding, thermoforming, prepreg, liquid injection processes, automated tape placement, filament winding, pultrusion, additive manufacturing, and other processes. The material limits, design, and assembly requirements, as well as the processing constraints, are significantly important for the realisation of novel product development using a manufacturing process by simultaneously optimising reliability, safety, and other performance-related issues. The current thermoplastic material systems and manufacturing techniques still have plenty of room for optimisation and advancement. This reprint presents the latest scientific and technical advances in thermoplastic materials and their composites, processing, characterisation, product development, and manufacturing process parameter optimisations.

This edited volume, "Research on Corporate Sustainability", contains reports written by experts in their areas of specialization. The volume begins by introducing a report on the interim system theory of corporate sustainability, which fills in the gap in the predominantly empirical field of corporate sustainability, and is followed by three reports on organizational resilience that are widely regarded as sustainability outcomes. Another set of reports is concerned with sustainable tourism and community development, as sustainable community development can often be sustained by the people who live there. Finally, the edited volume concludes with two reports on sustainable supply chain management and climate finance, which are seen as critical aspects of sustainable development.

Microstructure design is key in targeting the desired material's properties. Contributions related to microstructure design and characterization are collected in this Topic, together with their relation to the mechanical, fatigue, wear and corrosion resistance of different kinds of metals and alloys. The goal of this Topic is to present contributions related to the relationship between the microstructure and properties of metals and alloys for different applications, including aeronautical and aerospace applications. Different process routes are considered (thermo-mechanical routes and additive manufacturing) in this Topic. Contributions related to welding are also included.

Among terrestrial ecosystems, forests play a dominant role in maintaining biodiversity and providing ecosystem functioning, such as nutrient cycling, carbon sequestration, and ecosystem stability. Over the past several decades, however, global forests are facing unprecedented pressure from climate change and anthropogenic disturbances, resulting in a high rate of biodiversity loss due to deforestation, fragmentation, and degradation. Determining how to maintain biodiversity is extremely urgent if we want to achieve the aims of the Convention on Biological Diversity (CBD) and the Sustainable Development Goals (SDGs). The complex structure, species interaction, heterogenic environment, and regional species pool all affect the spatial and temporal patterns of forest species, but it is still unclear how these effects maintain long-term forest biodiversity as forests undergo rapid variations in habitat features under global change. This reprint includes sixteen published articles related to the dynamics of forest spatial structure, community assembly, forest recovery patterns after disturbance, spatial distribution of species diversity, effects of abiotic and biotic variables on understory species diversity, and above- and below-ground biotic interactions. These studies cover different forest types across varied spatial and temporal scales, as well as different biological groups (plants, birds and microbes). We acknowledge all authors who contributed to this reprint "Maintenance of Forest Biodiversity" of Forests. We hope this reprint can improve our understanding of the underlying mechanisms of forest biodiversity maintenance.

The aim of this reprint is to report on new scenarios, technologies, and applications related to the concept of the Internet of Everything and discuss challenges and risks.We introduced a wide range of topics related to emerging technologies. This reprint includes research on vendor-managed inventory mechanisms based on the SCADA of the Internet of Things, in-memory computing architecture for a convolutional neural network, face prediction system for missing children in a smart city safety network, anomaly electricity usage behavior in residence using an autoencoder, cloud-edge-smart IoT architecture for speeding up the deployment of neural network models, generative adversarial network and diverse feature extraction methods to enhance the classification accuracy of the tool-wear status, classifying conditions of speckles and wrinkles on the human face using a deep learning approach, repetition with learning approaches in massive machine-type communications, GDPR personal privacy security mechanism for smart home systems, and the development of an autonomous vehicle training and verification system. These articles demonstrate the rapid advances being made in the field of electronics and highlight the potential for these technologies to impact our daily lives.

Current advances in the knowledge of nonlinear dynamical networks, systems and processes, as well as their unified repercussions, allow us to include some typical complex natural phenomena, from the nanoscale to an extra-galactic scale, in an unitarian comprehensive manner. In other words, the physical, biological and financial data, as well as technological ones (mechanical or electronic devices), of complex systems available today can be managed by the same unique conceptual approach, both analytically and through a computer simulation, using effective nonlinear dynamics procedures. This volume collected some important advances in the fields of fractal curves, fractal analysis and fractional calculus, as well as new solutions of fractal differential equations. The works edited in the present technical publication are those that appeared in the Fractal and Fractional journal, in a Special Issue of the same name.

With the development of computer technology and communication technology, various industries have collected a large amount of data in different forms, so-called big data. How to obtain valuable knowledge from these data is a very challenging task. Machine learning is such a direct and effective method for big data analytics. In recent years, a variety of advanced machine learning technologies have emerged, and they continue to play important roles in the era of big data.Considering advanced machine learning and big data together, we have selected a series of relevant works in this Special Issue to showcase the latest research advancements in this field. Specifically, a total of thirty-three articles are included in this Special Issue, which can be roughly categorized into six groups: time series analysis, evolutionary computation, pattern recognition, computer vision, image encryption, and others.

This reprint focuses on the current progress in sports medicine, with a specific interest in surgery, exercise therapy, and multi-disciplinary research.With the advancement of society, more attention is paid to the quality of life, which emphasizes the importance of sports and exercise. Correspondingly, there is a great need for sports medicine. This issue collected novel findings on sports medicine in surgery, conservative therapy, and the application of exercise training in other disorders

This reprint is the result of a Special Issue, which took place in the International Journal of Environmental Research and Public Health (IJERPH) during 2022-2023. The general topic of the reprint discusses the different uses, protection and promotion of food, always from a broad perspective, through 15 innovative research papers, from both qualitative and quantitative methodological approaches.

This Special Issue deals with the field of intelligent soft sensors that enable the online estimation of nonmeasurable process variables. Soft sensors or virtual sensors are common names for software algorithms in which multiple measurements are processed together. Typically, soft sensors are based on control theory and are also referred to as state observers. There may be dozens or even hundreds of measurements from hard sensors (big data). The interaction of signals can be used to compute new quantities that cannot be measured directly online or are difficult and expensive to measure. Soft sensors are particularly useful in data fusion, combining measurements of different characteristics and dynamics. They can be used for fault diagnosis (self-analysis, self-calibration, and self-maintenance) as well as for control applications. Well-known software algorithms that can be seen as soft sensors include, for example, Kalman filters. More recent implementations of soft sensors use neural networks, fuzzy logic, models based on evolving clustering, partial least squares, etc. In the digitized factories of the future, intelligent sensors represent one of the core building blocks for automating and optimizing production, as they make production more efficient in every respect.

The chemistry of natural products is rich in diversity, which can be noted from several perspectives. Plants, fungi, and marine organisms represent sources of small molecules characterized by unique complexity related to their varied scaffolds, functional groups, and stereochemistry. At the same time, extraction, de novo synthesis, derivatization, and semi-synthetic approaches represent challenging tasks for organic chemists. In parallel, analytical profiling of the content of organic compounds and microelements in natural matrices pushes experimental techniques to the edge of their potential due to the complex tasks involved in sample preparation and data elaboration. Additionally, flavonoids, alkaloids, and terpenes, as well as their semisynthetic derivatives, attract the interest of medicinal chemists due to their beneficial biological effects, which include antioxidant, antiproliferative, antibacterial, and anti-inflammatory activities. This Special Issue aimed to collect original contributions to describe the extraction, structural elucidation, and synthesis of natural, semisynthetic, and nature-inspired synthetic molecules. Moreover, articles that discuss the analysis of the content and bioactivity of natural compounds in complex matrices, as well as review articles that focus on the chemistry of natural products, were considered in combination with research articles that describe significant results in terms of their innovative synthetic and extractive, as well as advanced analytical, techniques (chromatography, 1D and 2D NMR, mass spectrometry, IR and UV spectroscopy, etc.).

Landscapes and cultural heritage have faced many challenges over time, including modifications and degradation that appear with time, overlaps with other challenges not previously observed, and the influence of cities and management. One of the most visible and globally discussed challenges is climate change. Therefore, there is an urgent need to launch initiatives to tackle climate change and other current challenges from the perspective of landscape and cultural heritage protection. This Special Issue presents selected papers of studies conducted in relation to the 28th Conference on the Series of Garden Art and Historical Dendrology entitled "Climate Change and Current Challenges for Landscapes and Cultural Heritage" that was held on 28 and 29 October 2021. This collection serves as a platform for the exchange of experiences among researchers from different scientific domains.

Numerical methods have become crucial in recent years and have been applied in many research fields. Among these, environmental and energy research has become increasingly relevant. This Special Issue comprises a recent advances in research relating to numerical modeling applied to energy and environment.

This Special Issue of Religions focuses on the epistemology of religious experience. The overall driving question is the question as to what evidential force religious experiences have. This discussion involves several subtopics, including the following: (1) In what ways is religious experience like other kinds of experience? (2) To what extent does religious experience influence religious doctrine, and to what extent is it influenced by it? (3) What are the implications of religious diversity/disagreement for claims of religious experience? (4) How, if in any way, has the cognitive science of religion shed light on these issues? This issue approaches these questions from a variety of religious traditions, with input from a variety of academic disciplines. The result is a collection of high-quality papers that can inform further research in a variety of academic fields.

The increase in the volume of industrially processed products in the global food supply has coincided with an increasing prevalence of obesity and non-communicable diseases in many countries, suggesting that ultra-processed food consumption may be detrimental for human health. However, studies are still limited and underline the need to better understand the main determinants of their consumption and the mechanisms that may explain the associations between these products and human health. This Special Issue collected new studies investigating the relationship between the consumption of ultra-processed foods, diet quality and human health, including those aiming to: Develop new tools to better determine the rate of consumption of ultra-processed foods in the population; Investigate the rate of consumption of ultra-processed foods in different subgroups of the population, including subjects following different dietary patterns; Analyse the relationship between the consumption of ultra-processed foods and markers of health status; Explore possible mechanisms behind associations between the consumption of processed foods and healthBy providing up-to-date assessments of ultra-processed foods consumption and health implications, these reports will contribute to understanding if future public health nutrition policies are needed.

This Special Issue, "Advances in Environmental Applied Physics", collected original papers from eminent researchers in the field of environmental pollutants, which constitute a health risk to the population, increasing the likelihood of incurring cancer.

Plants under natural conditions often face multiple stresses, including drought, salinity, temperature extremes, submergence stress, bacteria, viruses, fungi, insects, etc. These biotic and abiotic stresses negatively influence plant growth and productivity. Various approaches have recently been used to overcome stresses in plants. It is necessary to evaluate and explore how diverse molecular techniques can be applied to different biological studies to improve biotic and abiotic stress tolerance in plants. This will help reduce production losses and increase crop tolerance to various stresses. It is now the time to make a difference by developing plants that can withstand biotic and abiotic stresses.

"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.

The Special Issue constitutes the collection of the selected papers, which results were presented during the XVIII Conference on Automation, Operation and Maintenance of Control and Communication Systems ASMOR 2022. The conference took place in W¿adys¿awowo (Poland) on 12-14 October 2022. The scope of the conference was mainly focused on automation and exploitation aspects of the control and communications systems. In order to meet the highest quality standards for published papers, only the articles selected by the ASMOR Scientific Committee and the Electronics Editors were qualified for an extensive reviewing process.

Plants under natural conditions often face multiple stresses, including drought, salinity, temperature extremes, submergence stress, bacteria, viruses, fungi, insects, etc. These biotic and abiotic stresses negatively influence plant growth and productivity. Various approaches have recently been used to overcome stresses in plants. It is necessary to evaluate and explore how diverse molecular techniques can be applied to different biological studies to improve biotic and abiotic stress tolerance in plants. This will help reduce production losses and increase crop tolerance to various stresses. It is now the time to make a difference by developing plants that can withstand biotic and abiotic stresses.

The concept of distance is important for establishing the degree of similarity and/or closeness between functions, populations, or distributions. As a result, distances are related to inferential statistics, including problems related to both estimation and hypothesis testing, as well as modelling with applications in regression analysis, multivariate analysis, actuarial science, portfolio optimization, survival analysis, reliability theory, and many other areas. Thus, entropy and divergence measures are always a central concern for scientists, researchers, medical experts, engineers, industrial managers, computer experts, data analysts, and other professionals.This reprint focuses on recent developments in information and divergence measures and presents new theoretical issues as well as solutions to important practical problems and case studies illustrating the great applicability of these innovative techniques and methods. The contributions in this reprint highlight the diversity of topics in this scientific field.

With the advancements in the medical and scientific fields, the global community has acquired a comprehensive understanding about brain insults and pathologies. In addition, new findings and discoveries are being made globally every day, which keep our curiosity high and drive a knowledge gain. Any brain insult or pathology is multifactorial, including a cascade of inflammation, necrotic, and apoptotic pathways; can be influenced by genetic or environmental factors; and may lead to chronic neurodegeneration or disabilities. This Special Issue, entitled "Brain Injury and Neurodegeneration: Molecular, Functional, and Translational Approach", has addressed various important aspects of brain injury and neurodegeneration, such as TBI, cerebral hypoxia, epilepsy, AD, and SARS-CoV-2-mediated brain damage. It received appreciable global response, and published 18 peer-reviewed articles, including 10 research articles and 8 reviews. Briefly, it explores the recent coronavirus infection-mediated cerebral damage; discusses the mechanism of TBI, ischemia, hypoxia, and epilepsy; talks about neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease and CONDCA; and, finally, reviews the translational values of phytochemicals in brain pathologies. In conclusion, this Special Issue provides a unique review on brain injury and neurodegeneration, and will be a good tool in enhancing knowledge in terms of brain disease-related pathology, mechanisms, and translational approach.

This Proceedings reprint is a collection of papers from the E-Textiles 2022 Conference and represents the state of the art from both academia and industry in the development of smart fabrics that incorporate electronic and sensing functionality. The Proceedings reprint presents a wide range of applications of the technology, including wearable textile devices for healthcare applications such as ECG measurements and functional electrical stimulation. Manufacturing approaches include printed smart materials, knitted e-textiles and flexible electronic circuit assembly within fabrics and garments. Supplying power is a constant challenge for all wireless wearable technologies, and therefore this collection includes papers on triboelectric energy harvesting and zinc-ion batteries fabricated on top of textile substrates.